• Journal of Nutrition and Health
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• v.56 no.5
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• pp.455-468
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• 2023

Purpose: Abeliophyllum distichum (A.distichum) is a plant native to Korea. In this study, we investigated the mechanism of antioxidant and anti-inflammatory effects of the leaf extract of A.distichum. Methods: The antioxidant capacity of the A.distichum leaf extract was determined based on the total polyphenol content, 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay, and the ferric reducing antioxidant power (FRAP) assay. The anti-inflammatory effects of the A.distichum leaf extract were evaluated by measuring the production of nitric oxide (NO) and the expression levels of proinflammatory cytokines including tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 using the enzyme-linked immunosorbent assay (ELISA) and reverse transcription quantitative real-time PCR (RT-qPCR). In addition, the expression of heme oxygenase-1 (HO-1), nuclear transcription factor-erythroid 2 related factor (Nrf2), inducible nitric oxide synthase (iNOS), and cyclooxygenase 2 (COX-2), as well as the activation of nuclear factorkappa B (NF-ĸB) were examined using the western blot analysis. Results: The total polyphenol content of the A.distichum leaf extract was 329.89 ± 30.17 gallic acid equivalents mg/g and the DPPH and ABTS scavenging activities were 55% and 70%, respectively. Additionally, the FRAP value of the extract was 743.68 ± 116.59 mg/mL. After 12-hour treatment with the A.distichum leaf extract, there was a tendency for the Nrf2 expression to increase, and the expression of HO-1 was significantly elevated in the RAW264.7 cells. The A.distichum leaf extract treatment resulted in decreased levels of NO, TNF-α, IL-6, and IL-1β, as well as reduced expression of iNOS and COX-2, along with inhibition of NF-κB activation in lipopolysaccharide-stimulated RAW264.7 cells. Conclusion: These results suggest that the A.distichum leaf extract exerts antioxidative and anti-inflammatory effects by upregulating the expression of HO-1 and downregulating NF-κB activation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.935-940
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• 2023

Digital-twin technology is emerging as an innovative solution for all industries, including manufacturing and production lines. Therefore, this paper optimizes all the energy used in a biomass plant based on unused resources. We will then implement a digital-twin prototype for biomass plants and evaluate its performance in order to improve the efficiency of plant operations. The proposed digital-twin prototype applies a standard communication platform between the framework and the gateway and is implemented to enable real-time collaboration. and, define the message sequence between the client server and the gateway. Therefore, an interface is implemented to enable communication with the host server. In order to verify the performance of the proposed prototype, we set up a virtual environment to collect data from the server and perform a data collection evaluation. As a result, it was confirmed that the proposed framework can contribute to energy optimization and improvement of operational efficiency when applied to biomass plants.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.207-228
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• 2023

After COVID-19, organizations have widely adopted platforms such as zoom or developed their proprietary online real-time systems for remote work, with recent forays into incorporating the metaverse for meetings and publicity. While ongoing studies investigate the impact of avatar customization, expansive virtual environments, and past virtual experiences on participant satisfaction within virtual reality or metaverse settings, the utilization of the metaverse as a dedicated workspace is still an evolving area. There exists a notable gap in research concerning the factors influencing the performance of the metaverse as a workspace, particularly in non-immersive work-type metaverses. Unlike studies focusing on immersive virtual reality or metaverses emphasizing immersion and presence, the majority of contemporary work-oriented metaverses tend to be non-immersive. As such, understanding the factors that contribute to the success of these existing non-immersive metaverses becomes crucial. Hence, this paper aims to empirically analyze the factors impacting personal outcomes in the non-immersive metaverse workspace and derive implications from the results. To achieve this, the study adopts the Embodied Social Presence (ESP) model as a theoretical foundation, modifying and proposing a research model tailored to the non-immersive metaverse workspace. The findings validate that the impact of presence on task engagement and task involvement exhibits a moderating effect based on the metaverse platform used. Following interviews with participants engaged in non-immersive metaverse workplaces (specifically Gather Town and Ifland), a survey was conducted to gather comprehensive insights.

• Composites Research
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• v.36 no.6
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• pp.429-434
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• 2023

In this study, aimed at improving the existing acoustic emission sensor for real time monitoring, a macro-fiber composite (MFC) transducer was employed as the acoustic emission sensor in the gas leak detection system. Prior to implementation, structural analysis was conducted to optimize the MFC's design. Consequently, the flexibility of the MFC facilitated excellent adherence to curved pipes, enabling the reception of acoustic emission (AE) signals without complications. Analysis of AE signals revealed substantial variations in parameter values for both high-pressure and low-pressure leaks. Notably, in the parameters of the Fast Fourier Transform (FFT) graph, the change amounted to 120% to 626% for high-pressure leaks compared to the case without leaks, and approximately 9% to 22% for low-pressure leaks. Furthermore, depending on the distance from the leak site, the magnitude of change in parameters tended to decrease as the distance increased. As the results, in the future, not only will it be possible to detect a leak by detecting the amount of parameter change in the future, but it will also be possible to identify the location of the leak from the amount of change.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.1-16
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• 2024

Alvin Toffler mentioned that it is important for future society to keep pace with synchronization and that time deviations can hinder social development. As we experience the new normal era of untact, we have experienced an increase in non-face-to-face contact and accelerated digital transformation. Amid these rapid changes, we can maintain the need for synchronization or change in space. Therefore, we would like to study what kind of settlements people create and choose. We looked at the metaverse as an object that could indirectly find out about this, and used the content called "Animal Crossing" to collect data related to the spatial form of the metaverse. Sampling utilized a judgment sampling method during non-probability sampling to alleviate differences due to the progress of the game. The collected data was classified according to floor plan and location type and briefly organized through descriptive statistics. After matching each facility by use, data was constructed by setting coordinates for each cluster and listing them. This data was interpreted graphically on the coordinate plane for each cluster, and Euclidean analysis was performed to analyze the relationships between clusters and residential choice using a Euclidean matrix. As a result of the analysis, it could be interpreted that efficiency was pursued by arranging similar functions in close proximity. Nevertheless, when choosing a residence, it was interpreted that the intention was to create a community through arrangement adjacent to residents rather than efficiency or convenience. Due to the differences between the metaverse and the real world, it is expected that there will be limitations in equating it with reality. However, through the space expressed in the virtual world by people who are far away from the constraints of reality, we can indirectly know the wishes that we have not been able to express due to our lack of awareness.

• Animal Bioscience
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• v.37 no.3
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• pp.522-535
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• 2024

Objective: Transition period is considered from 3 weeks prepartum to 3 weeks postpartum, characterized with dramatic events (endocrine, metabolic, and physiological) leading to occurrence of production diseases (negative energy balance/ketosis, milk fever etc). The objectives of our study were to analyze the periodic concentration of serum beta-hydroxy butyric acid (BHBA), glucose and oxidative markers along with identification, and validation of the putative markers of negative energy balance in buffaloes using in-silico and quantitative real time-polymerase chain reaction (qRT-PCR) assay. Methods: Out of 20 potential markers of ketosis identified by in-silico analysis, two were selected and analyzed by qRT-PCR technique (upregulated; acetyl serotonin o-methyl transferase like and down regulated; guanylate cyclase activator 1B). Additional two sets of genes (carnitine palmotyl transferase A; upregulated and Insulin growth factor; downregulated) that have a role of hepatic fatty acid oxidation to maintain energy demands via gluconeogenesis were also validated. Extracted cDNA (complementary deoxyribonucleic acid) from the blood of the buffaloes were used for validation of selected genes via qRTPCR. Concentrations of BHBA, glucose and oxidative stress markers were identified with their respective optimized protocols. Results: The analysis of qRT-PCR gave similar trends as shown by in-silico analysis throughout the transition period. Significant changes (p<0.05) in the levels of BHBA, glucose and oxidative stress markers throughout this period were observed. This study provides validation from in-silico and qRT-PCR assays for potential markers to be used for earliest diagnosis of negative energy balance in buffaloes. Conclusion: Apart from conventional diagnostic methods, this study improves the understanding of putative biomarkers at the molecular level which helps to unfold their role in normal immune function, fat synthesis/metabolism and oxidative stress pathways. Therefore, provides an opportunity to discover more accurate and sensitive diagnostic aids.

• Animal Bioscience
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• v.37 no.4
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• pp.609-621
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• 2024

Objective: Hair follicle stem cells (HFSCs) differentiation is a critical physiological progress in skin hair follicle (HF) formation. Goat HFSCs differentiation is one of the essential processes of superior-quality brush hair (SQBH) synthesis. However, knowledge regarding the functions and roles of miR-133a-3p and miR-145-5p in differentiated goat HFSCs is limited. Methods: To examine the significance of chi-miR-133a-3p and chi-miR-145-5p in differentiated HFSCs, overexpression and knockdown experiments of miR-133a-3p and miR-145-5p (Mimics and Inhibitors) separately or combined were performed. NANOG, SOX9, and stem cell differentiated markers (β-catenin, C-myc, Keratin 6 [KRT6]) expression levels were detected and analyzed by using real-time quantitative polymerase chain reaction, western blotting, and immunofluorescence assays in differentiated goat HFSCs. Results: miR-133a-3p and miR-145-5p inhibit NANOG (a gene recognized in keeping and maintaining the totipotency of embryonic stem cells) expression and promote SOX9 (an important stem cell transcription factor) expression in differentiated stem cells. Functional studies showed that miR-133a-3p and miR-145-5p individually or together overexpression can facilitate goat HFSCs differentiation, whereas suppressing miR-133a-3p and miR-145-5p or both inhibiting can inhibit goat HFSCs differentiation. Conclusion: These findings could more completely explain the modulatory function of miR-133a-3p and miR-145-5p in goat HFSCs growth, which also provide more understandings for further investigating goat hair follicle development.

• Animal Bioscience
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• v.37 no.3
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• pp.509-521
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• 2024

Objective: It was shown that microRNAs (miRNAs) play an important role in milk protein synthesis. However, the post-transcriptional regulation of casein expression by exogenous miRNA (xeno-miRNAs) in ruminants remains unclear. This study explores the regulatory roles of alfalfa xeno-miR162 on casein synthesis in bovine mammary epithelial cells (bMECs). Methods: The effects of alfalfa xenomiR-162 and G protein subunit gamma 11 (GNG11) on proliferation and milk protein metabolism of bMECs were detected by 5-Ethynyl-2'-Deoxyuridine (EdU) staining, flow cytometry, cell counting kit-8 (CCK-8), enzyme-linked immunosorbent assay, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blot. Dual-luciferase reporter assay was used to verify the targeting relationship between GNG11 and xenomiR-162. Results: Results showed that over-expression of xenomiR-162 inhibited cell proliferation but promoted apoptosis, which also up-regulated the expression of several casein coding genes, including CSN1S1, CSN1S2, and CSN3, while decreasing the expression of CSN2. Furthermore, the targeting relationship between GNG11 and xenomiR-162 was determined, and it was confirmed that GNG11 silencing also inhibited cell proliferation but promoted apoptosis and reduced the expression of casein coding genes and genes related to the mammalian target of rapamycin (mTOR) pathway. Conclusion: Alfalfa xenomiR-162 appears to regulate bMECs proliferation and milk protein synthesis via GNG11 in the mTOR pathway, suggesting that this xeno-miRNA could be harnessed to modulate CSN3 expression in dairy cows, and increase κ-casein contents in milk.

• Information Systems Review
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• v.23 no.4
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• pp.103-125
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• 2021

Mobility services are rapidly developing along with information and communication technology (ICT) innovation. Recently, the on-demand mobility platform market is growing, and an environment is provided in which users can call services more conveniently and check the connection status in real time using smartphones. This study investigates the current status of users' perceptions and experiences of car-hailing mobility services such as KAKAO Taxi and UT Taxi, and it analyzes the factors affecting the intention to continuously use the car-hailing service, focusing on environmental and instrumental benefits and trust in driver and platform. In particular, this study examines whether the significance of the relationship between influencing factors and continuous use intention could vary depending on the degree of innovativeness and ICT utilization. The results of this study showed that perceived benefits (environmental benefits and convenience and economic instrumental benefits) and trust in driver had significant effects on increasing trust in platform. It was analyzed that the higher the trust in platform, the higher the intention to continuously use the car-hailing service. Furthermore, the influence of perceived environmental benefits and economic benefits on the trust in platform was different depending on the degree of individual innovativeness, and the influence of convenience and economic benefits on the trust in platform varied depending on the degree of ICT utilization. Referring to the results of this study, mobility service providers can better understand the current status of users' perceptions and trust for car-hailing services, and implement service promotion strategies suitable for individual characteristics.